This competitive renewal application seeks to continue a project on the genetics of Alzheimer's disease (AD). As part of the funded project we performed genome-wide association study (GWAS) on our case-control sample that has contributed to the identification of multiple novel loci for AD as part of national and internationl collaborations. In addition to GWASs, we also performed several association studies on candidate genes that resulted in >50 publications during the current grant period. Confirmed loci identified for AD risk using the case-control association design account for only ~30% of the phenotypic variance. An alternative approach focusing on AD quantitative phenotypes/endophenotypes may help to identify additional genes for AD, as this approach can be more powerful than using the binary case-control design. As part of our preliminary data for this renewal, we have completed GWASs on four AD-related phenotypes: deposition of A in the brain measured by amyloid imaging, short-term disease progression measured by change in Mini-Mental State Examination (MMSE) score over 12 months, disease progression measured by time to reach MMSE 9 score (indicator of moderate to severe AD), and survival time in AD. We have identified novel loci for each AD- related phenotype. Using pathway analysis we have also identified multiple potentially novel candidate genes in the networks of GWAS-implicated genes. Since GWAS arrays use an indirect approach that relies on linkage disequilibrium to detect association signals, rarely are the identified significant variants the causal variants. Thu, it is important to resequence the candidate gene regions implicated by GWASs and those that participate in their networks in order to characterize the full spectrum of common, low-frequency and rare causal variants associated with AD-related phenotypes. The objective of this renewal application is to perform targeted resequencing of selected top gene regions implicated by GWASs and additional candidate genes in the networks of GWAS-implicated genes in order to identify causal variants associated with four AD-related phenotypes. Replication of significant variants obtained in the discovery stage will be sought in independent sets of replication samples. Finally, we will examine the functional nature of the identified significant variants usin bioinformatics tools and brain gene expression data. The successful completion of the proposed comprehensive studies will likely lead to the identification of new AD-related genes/variants.